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Role-play simulations are a transdisciplinary method for engaging diverse stakeholders beyond traditional policy- and decision-making communities in an informed and inclusive public debate around the governance of complex socio-environmental challenges. 

Scenarios as a decision-making tool help us to better understand the implications of a wide range of future possibilities considering existing development, strategies, and global interdependencies. Scenarios should be co-produced with their users, most often planner and decision makers.

The Fair Mitigation Finance Explorer is the web app accompanying the paper 'Fairness considerations in global mitigation investments'. Users can select various indicators with a variety of weights to explore the ‘fair’ regional contributions to near-term regional mitigation investment needs. With this information, the web app determines the ‘fair-share’ regional contributions to their respective regional ‘cost-effective’ investment needs.

The Shared Socioeconomic Pathway (SSP) Extensions Explorer is a tool for visualizing and downloading quantitative elaborations of the Shared Socioeconomic Pathways (SSPs), which emerged in the literature since the publication of the original set (e.g., GDP, population) of SSP-related indicators. The tool hosts scenarios of indicators such as Gender Inequality Index, Governance, Rule of Law, Human Development Index, and Migration Flows.

Integrated Assessment Models (IAMs) develop long-term mitigation scenarios which play an essential role in the development of IPCC reports. These models, however, have been criticized for proposing solutions that are challenging to carry out due to a lack of consideration of social and institutional challenges. In the paper "A multidimensional feasibility evaluation of low-carbon scenarios by person" (Brutschin, et al., 2021), scientists proposed a versatile, multidimensional framework that allows for comparisons between decarbonization pathways by quantifying feasibility concerns. This online, interactive tool was developed to complement this paper and allows the user to examine this framework in more detail.

The new website is designed to provide latest information on climate mitigation and climate impacts, and aims to be a comprehensive resource for individuals, businesses, and policymakers looking to use some of the latest data from research on climate impacts and net zero mitigation pathways. The CSE website features a range of content, including and interactive map of climate change impacts, national and regional data dashboards of impacts and mitigation pathways, and interactive articles on a range of climate topics and countries.

Welcome to the world of PlantFATE, a novel eco-evolutionary vegetation model designed to unravel the intricate dynamics of forests and their response to environmental change. PlantFATE stands as a powerful tool to guide conservation efforts, inform policy decisions, and foster a deeper appreciation for the wonders of nature. Embark on a journey through the intricate tapestry of forest resilience with PlantFATE as your guide.

This application serves as an expansion of the Bayesian Reconstruction of Populations and Vital Rates by Educational Attainment (BayesEdu) project. Its objective is to integrate existing demographic data to generate accurate estimates of population sizes and vital rates categorized by educational attainment, while also considering associated uncertainties.

We provide a global spatially explicit characterization of terrestrial and marine habitat types, as defined in the International Union for Conservation of Nature (IUCN) habitat classification scheme, which is widely used in ecological analyses, including for assessing species’ Area of Habitat. The maps broaden our understanding of habitats globally, assist in constructing area of habitat (AOH) refinements and are relevant for broad-scale ecological studies and future IUCN Red List assessments.

A host of scientific chemistry and climate model experiments explore responses of the global atmosphere and climate systems to possible future changes in emissions of air pollutants and greenhouse gases. The Pollution Management research group (formerly AIR program) has used its GAINS model to develop a set of global emission fields of nine substances that provide consistent sets of future sectoral emissions for well-specified assumptions on economic development and the effectiveness of dedicated emission control policies.

A regional to global model designed to simulate and predict the dynamics of water quantity and quality under the influence of various drivers including; climate change, land-use transitions, socio-economic developments, and policy interventions. 

The Integrated Catastrophe Analysis and Management Modeling (ISCRiMM) approach addresses systemic risks by analyzing socio-economic and structural vulnerabilities, employing statistical and machine learning methods, and enabling stakeholders to update vulnerability indices for effective risk management.

While the full model is under review and development, this is an abbreviated description of its main purpose, components, assumptions, and variables, but without some details and equations.

WADE provides easy access to the innovative dynamic metrics of aging developed at IIASA. These metrics take the changing characteristics of people into account, thereby providing policymakers, researchers, and educators with a view of aging appropriate for our changing demographic environment. All indicators are based on data from the UN’s World Population Prospects 2022 and 2024. They cover the period 1950 to 2100 and are disaggregated by region, subregion, and country. Both types of indicators can also be produced with user-defined data.

The DisruptSC model assesses the indirect economic impacts of disasters by explicitly quantifying the disturbances on supply chains. It simulates, in space and time, how transport infrastructure disruptions perturb the flows of goods in supply chains and how these perturbations affect households, firms, and trade.

Pathfinder is designed to fill a perceived gap within the existing simple climate models by fulfilling three key requirements: (1) the capacity to be calibrated using Bayesian inference, (2) the capacity to be coupled with integrated assessment models (IAMs), and (3) the capacity to explore a very large number of climate scenarios to narrow down those compatible with limiting climate impacts.

A historical database of energy use by country or region, energy level, sector, energy carrier, and end-use type.

The Energy and Carbon Emissions Inventory Database (ECDB) compares major global inventories of primary energy use and carbon emissions.

The SD-ET analysis provides a novel methodological framework of using observed historical patterns of technological change to test the plausibility of future scenarios of technological change to meet climate change mitigation goals.

MAGICC is a reduced complexity Earth system model that has been widely used in climate science for over three decades, most notably in multiple IPCC reports. It is most often used in a probabilistic setup, providing information not only about our best-estimate of future climate change but also the uncertainty that arises from interactions between the Earth system’s many components. MAGICC is also as the climate component in multiple integrated assessment models (IAMs).